Senior High-Performance AI Engineer: GPU Agent Systems in Redmond

Senior High-Performance AI Engineer: GPU Agent Systems in Redmond

Redmond Full-Time 123750 - 151250 $ / year (est.) On-site
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At a Glance

  • Tasks: Build groundbreaking multi-agent systems and design agentic runtimes for AI workloads.
  • Company: Join NVIDIA, a leader in AI technology and innovation.
  • Benefits: Competitive salary, health benefits, and opportunities for professional growth.
  • Other info: Collaborative environment with exciting projects and career advancement opportunities.
  • Why this job: Make a real impact in AI while working with cutting-edge GPU technologies.
  • Qualifications: 8+ years in AI systems, strong C/C++ and Python skills required.

The predicted salary is between 123750 - 151250 $ per year.

NVIDIA Corporation in Redmond, WA is seeking a Senior High Performance AI Engineer to build groundbreaking multi-agent systems for the CUDA ecosystem.

You will design agentic runtimes and collaborate with software and hardware teams to accelerate AI workloads.

The role requires 8+ years in AI systems, strong C/C++ and Python skills, and hands-on GPU optimization experience.

You will contribute to evaluation frameworks and cross-stack collaboration across AI workloads.

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Senior High-Performance AI Engineer: GPU Agent Systems in Redmond employer: NVIDIA Corporation

NVIDIA Corporation is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the rapidly evolving field of AI solutions. Located at the forefront of technology, employees benefit from extensive growth opportunities, competitive compensation, and the chance to work alongside industry leaders in government and research sectors, making a meaningful impact on advanced technology engagements.

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Contact Details:

NVIDIA Corporation Recruitment Team

We think you need these skills to ace Senior High-Performance AI Engineer: GPU Agent Systems in Redmond

AI Systems Development
C/C++ Programming
Python Programming
GPU Optimization
Multi-Agent Systems Design
CUDA Ecosystem Knowledge
Evaluation Frameworks Contribution